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An example of a Kaplan–Meier plot for two conditions associated with patient survival. The Kaplan–Meier estimator, [1] [2] also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a ...
S(t) is theoretically a smooth curve, but it is usually estimated using the Kaplan–Meier (KM) curve. The graph shows the KM plot for the aml data and can be interpreted as follows: The x axis is time, from zero (when observation began) to the last observed time point. The y axis is the proportion of subjects surviving. At time zero, 100% of ...
Paul Meier (July 24, 1924 – August 7, 2011) [1] was a statistician who promoted the use of randomized trials in medicine. [2] [3]Meier is known for introducing, with Edward L. Kaplan, the Kaplan–Meier estimator, [4] [5] a method for measuring how many patients survive a medical treatment from one duration to another, taking into account that the sampled population changes over time.
A parametric model of survival may not be possible or desirable. In these situations, the most common method to model the survival function is the non-parametric Kaplan–Meier estimator. This estimator requires lifetime data.
It can be thought of as the kaplan-meier survivor function for a particular year, divided by the expected survival rate in that particular year. That is typically known as the relative survival (RS). If five consecutive years are multiplied, the resulting figure would be known as cumulative relative survival (CRS). It is analogous to the five ...
The logrank test is based on the same assumptions as the Kaplan-Meier survival curve—namely, that censoring is unrelated to prognosis, the survival probabilities are the same for subjects recruited early and late in the study, and the events happened at the times specified. Deviations from these assumptions matter most if they are satisfied ...
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Kaplan–Meier estimator [ edit ] The Dvoretzky–Kiefer–Wolfowitz inequality is obtained for the Kaplan–Meier estimator which is a right-censored data analog of the empirical distribution function